LLM-Powered Educational Content Summarization System
Budget: ₹5,000 – ₹15,000 INR
I need a system that uses a Large Language Model to summarize and condense lengthy educational materials, such as full-length lectures and PDFs, into concise and easily digestible formats like video snippets, infographics, and text summaries. The goal is to enhance learning efficiency by transforming complex information into byte-sized content.
Key requirements:
- The system should be able to process a variety of sources for content generation, including full-length lectures, PDFs, and web articles.
- It should also be capable of incorporating interactive elements into the summarized content, such as quizzes, clickable links, and interactive diagrams.
Ideal skills and experience for the job:
- Proficiency in developing systems powered by Large Language Models.
- Experience with content summarization and transformation.
- Ability to create interactive elements within content.
- Familiarity with various educational resources and formats.
OCR for PDFs: Use advanced OCR technology (e.g., Tesseract, Google Vision API) to accurately extract text and images from scanned or image-based PDFs.
Speech-to-Text for Lectures: Implement state-of-the-art ASR (Automatic Speech Recognition) models (e.g., Whisper by OpenAI, Google Speech-to-Text) to transcribe lectures with high accuracy.
Web Scraping Pipelines: Develop reliable web scraping tools (using Puppeteer, Scrapy) for structured extraction of content from articles, ensuring compliance with copyright laws.
Dynamic Infographics: Integrate libraries (e.g., D3.js, Canva API) to generate interactive and visually appealing infographicsDeploy the system on a scalable cloud platform (AWS, GCP, or Azure) using container orchestration tools like Kubernetes for high availability.
Use message queues (e.g., Kafka, RabbitMQ) for handling concurrent requests.
Implement caching (e.g., Redis, Memcached) to improve response time for frequently accessed summaries.
b. Performance Optimization
Dynamic Workload Balancing: Implement load balancers to distribute incoming workloads evenly.
Processing Pipeline Optimization: Use asynchronous processing for resource-intensive tasks like summarization and video generation.
c. Data Privacy & Compliance
Ensure compliance with privacy regulations like GDPR or FERPA by anonymizing user data.
Encrypt data in transit and at rest using protocols like TLS and AES.
Key requirements:
- The system should be able to process a variety of sources for content generation, including full-length lectures, PDFs, and web articles.
- It should also be capable of incorporating interactive elements into the summarized content, such as quizzes, clickable links, and interactive diagrams.
Ideal skills and experience for the job:
- Proficiency in developing systems powered by Large Language Models.
- Experience with content summarization and transformation.
- Ability to create interactive elements within content.
- Familiarity with various educational resources and formats.
OCR for PDFs: Use advanced OCR technology (e.g., Tesseract, Google Vision API) to accurately extract text and images from scanned or image-based PDFs.
Speech-to-Text for Lectures: Implement state-of-the-art ASR (Automatic Speech Recognition) models (e.g., Whisper by OpenAI, Google Speech-to-Text) to transcribe lectures with high accuracy.
Web Scraping Pipelines: Develop reliable web scraping tools (using Puppeteer, Scrapy) for structured extraction of content from articles, ensuring compliance with copyright laws.
Dynamic Infographics: Integrate libraries (e.g., D3.js, Canva API) to generate interactive and visually appealing infographicsDeploy the system on a scalable cloud platform (AWS, GCP, or Azure) using container orchestration tools like Kubernetes for high availability.
Use message queues (e.g., Kafka, RabbitMQ) for handling concurrent requests.
Implement caching (e.g., Redis, Memcached) to improve response time for frequently accessed summaries.
b. Performance Optimization
Dynamic Workload Balancing: Implement load balancers to distribute incoming workloads evenly.
Processing Pipeline Optimization: Use asynchronous processing for resource-intensive tasks like summarization and video generation.
c. Data Privacy & Compliance
Ensure compliance with privacy regulations like GDPR or FERPA by anonymizing user data.
Encrypt data in transit and at rest using protocols like TLS and AES.